---
title: Frequently Asked Questions
description: "Learn more about TensorZero: how it works, why we built it, and more."
---

<Tip>

**Next steps?**
The [Quickstart](/quickstart/) shows it's easy to set up an LLM application with TensorZero.

**Questions?**
Ask us on [Slack](https://www.tensorzero.com/slack) or [Discord](https://www.tensorzero.com/discord).

**Using TensorZero at work?**
Email us at [hello@tensorzero.com](mailto:hello@tensorzero.com) to set up a Slack or Teams channel with your team (free).

</Tip>

## Technical

<Accordion title="Why is the TensorZero Gateway a proxy instead of a library?">

TensorZero's proxy pattern makes it agnostic to the application's tech stack, isolated from the business logic, more composable with other tools, and easy to deploy and manage.

Many engineers are (correctly) wary of marginal latency from such a proxy, so we built the gateway from the ground up with performance in mind.
In [Benchmarks](/gateway/benchmarks/), it achieves sub-millisecond P99 latency overhead under extreme load.
This makes the gateway fast and lightweight enough to be unnoticeable even in the most demanding LLM applications, especially if deployed as a sidecar container.

</Accordion>

<Accordion title="How is the TensorZero Gateway so fast?">

![TensorZero Crab](./tensorzero-crab.png)

The TensorZero Gateway was built from the ground up with performance in mind.
It was written in Rust 🦀 and optimizes many common bottlenecks by efficiently managing connections to model providers, pre-compiling schemas and templates, logging data asynchronously, and more.

It achieves &lt;1ms P99 latency overhead under extreme load.
In [Benchmarks](/gateway/benchmarks/), LiteLLM @ 100 QPS adds 25-100x+ more latency than the TensorZero Gateway @ 10,000 QPS.

</Accordion>

<Accordion title="Why did you choose ClickHouse as TensorZero's analytics database?">

ClickHouse is open source, [extremely fast](https://www.vldb.org/pvldb/vol17/p3731-schulze.pdf), and versatile.
It supports diverse storage backends, query patterns, and data types, including vector search (which will be important for upcoming TensorZero features).
From the start, we designed TensorZero to be easy to deploy but able to grow to massive scale.
ClickHouse is the best tool for the job.

</Accordion>

## Project

<Accordion title="Who is behind TensorZero?">

We're a small technical team based in NYC. [Work with us →](https://www.tensorzero.com/jobs/)

#### Founders

[Viraj Mehta](https://virajm.com) (CTO) recently completed his PhD from CMU, with an emphasis on reinforcement learning for LLMs and nuclear fusion, and previously worked in machine learning at KKR and a fintech startup; he holds a BS in math and an MS in computer science from Stanford.

[Gabriel Bianconi](https://www.gabrielbianconi.com) (CEO) was the chief product officer at Ondo Finance ($20B+ valuation in 2024) and previously spent years consulting on machine learning for companies ranging from early-stage tech startups to some of the largest financial firms; he holds BS and MS degrees in computer science from Stanford.

</Accordion>

<Accordion title="How is TensorZero licensed?">

![TensorZero Freedom](./tensorzero-freedom.png)

TensorZero is open source under the permissive [Apache 2.0 License](https://github.com/tensorzero/tensorzero/blob/main/LICENSE).

</Accordion>

<Accordion title="How does TensorZero make money?">

<a href="https://www.youtube.com/watch?v=BzAdXyPYKQo" target="_blank">
  We don't.
</a>

We're lucky to have investors who are aligned with our long-term vision, so we're able to focus on building and snooze this question for a while.

We're inspired by companies like Databricks and ClickHouse.
One day, we'll launch a managed service that further streamlines LLM engineering, especially in enterprise settings, but open source will always be at the core of our business.

</Accordion>
